Number Systems for Deep Neural Network Architectures

Language: English

Published by Springer Nature Switzerland Okt 2023, 2023

3031381327 / 9783031381324

Series: Book 70 of 110 - Synthesis Lectures on Engineering, Science, and Technology

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This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides readers a comprehensive introduction to alternative number systems for more efficient representations of Deep Neural Network (DNN) data. Various number systems (conventional/unconventional) exploited for DNNs are discussed, including Floating Point (FP), Fixed Point (FXP), Logarithmic Number System (LNS), Residue Number System (RNS), Block Floating Point Number System (BFP),Dynamic Fixed-Point Number System (DFXP) and Posit Number System (PNS).The authors explore the impact of these number systems on the performance and hardware design of DNNs, highlighting the challenges associated with each number system and various solutions that are proposed for addressing them. 108 pp. Englisch.

Seller Inventory # 9783031381324

Title
Number Systems for Deep Neural Network Architectures
Author
Ghada Alsuhli
Publisher
Springer Nature Switzerland Okt 2023
Publication year
2023
Condition
Neu
Binding
Buch
Language
English
ISBN 10
3031381327
ISBN 13
9783031381324
Item weight
372 grams
Dimensions
246x173x12 mm
Series
Book 70 of 110: Synthesis Lectures on Engineering, Science, and Technology

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

AbeBooks seller since January 11, 2012

Shipping rates from Germany to U.S.A.

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First item£ 19.75£ 19.75
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BuchWeltWeit Ludwig Meier e.K.

Germany